Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A system, comprising: memory; and at least one processor coupled to the memory, the at least one processor configured to: receive, from a client device, contextual information indicating a pattern of files associated with the client device or a series of files associated with the client device, and performance information indicating at least one of: consumption of memory of the client device, consumption of processor cycles of the client device, configuration of at least one of hardware, software, firmware, or an operating system of the client device, input/output bandwidth of the client device, bandwidth of a network that is communicatively coupled to the client device, or latency associated with the network; infer a causation relationship between: the pattern of files associated with the client device or the series of files associated with the client device, and the performance information; and in response to the inferred causation relationship, provide, to the client device, configuration information that: identifies at least one of the following, which is configured to improve operating performance of the client device: at least one application, or at least one update; and is based at least in part on: the pattern of files associated with the client device or the series of files associated with the client device, the performance information, and an inference from a probability distribution over states in accordance with a classification scheme that maps an input attribute vector associated with an input to a confidence that the input belongs to a class, the input relating to at least one of the pattern of files associated with the client device, the series of files associated with the client device, or the performance information, the class corresponding to the configuration information.
A system monitors client device performance and file usage patterns to optimize system configuration. The system collects contextual data, including file patterns and series of files associated with the client device, along with performance metrics such as memory usage, processor cycles, hardware/software/firmware/OS configuration, I/O bandwidth, network bandwidth, and network latency. It analyzes this data to infer causal relationships between file usage and performance degradation. Based on these insights, the system generates configuration recommendations, such as suggesting specific applications or updates, to improve device performance. The recommendations are derived using probabilistic classification, where an input attribute vector—representing file patterns, performance data, or both—is mapped to a confidence score indicating the likelihood that a particular configuration change will belong to a class of effective solutions. The system dynamically adjusts configurations to enhance efficiency and responsiveness based on real-time data analysis.
2. The system of claim 1 , wherein the contextual information further indicates: a pattern of a type of at least one of software, firmware, an application, or an operating system being installed on the client device, or a series of the type.
3. The system of claim 1 , wherein the contextual information includes knowledge about a spike in third party searches associated with at least one of at least one hardware issue or at least one software issue; and wherein the at least one processor is configured to: infer a relationship between the knowledge about the spike in the third party searches and the performance information; and in response to the inferred relationship between the knowledge about the spike in the third party searches and the performance information, provide, to the client device, the configuration information further based at least in part on the knowledge about the spike in the third party searches.
4. The system of claim 1 , wherein the at least one processor is configured to, in response to the inferred causation relationship, anticipatorily provide, to the client device, the configuration information.
5. The system of claim 1 , wherein the contextual information includes knowledge about a spike in network queries associated with at least one of at least one hardware issue or at least one software issue; and wherein the at least one processor is configured to: infer a relationship between the knowledge about the spike in the network queries and the performance information; and in response to the inferred relationship between the knowledge about the spike in the network queries and the performance information, provide, to the client device, the configuration information further based at least in part on the knowledge about the spike in the network queries.
6. The system of claim 1 , wherein the contextual information includes knowledge about a spike in messages associated with at least one of at least one hardware issue or at least one software issue; and wherein the at least one processor is configured to: infer a relationship between the knowledge about the spike in the messages and the performance information; and in response to the inferred relationship between the knowledge about the spike in the messages and the performance information, provide, to the client device, the configuration information further based at least in part on the knowledge about the spike in the messages.
7. The system of claim 1 , wherein the at least one processor is configured to: receive information associated with at least one social network query performed by at least one third party about at least one of at least one hardware issue or at least one software issue associated with at least one of the contextual information or the performance information; infer a relationship between the performance information and the at least one of the at least one hardware issue or the at least one software issue that the at least one social network query is about to obtain correlation information; and provide, to the client device, the configuration information based at least in part on the correlation information.
8. The system of claim 1 , wherein the at least one processor is configured to: receive information indicating performance of a computing device that is different from the client device; and wherein the configuration information is further based at least in part on the information indicating the performance of the computing device.
9. A device-implemented method comprising: receiving, from a client device, contextual information indicating a pattern of files associated with the client device or a series of files associated with the client device, and performance information indicating at least one of: consumption of memory of the client device, consumption of processor cycles of the client device, configuration of at least one of hardware, software, firmware, or an operating system of the client device, input/output bandwidth of the client device, bandwidth of a network that is communicatively coupled to the client device, or latency associated with the network; inferring a causation relationship between: the pattern of files associated with the client device or the series of files associated with the client device, and the performance information; and in response to the inferred causation relationship, providing, to the client device, configuration information that: identifies at least one of the following, which is configured to improve operating performance of the client device: at least one application, or at least one update; and is based at least in part on: the pattern of files associated with the client device or the series of files associated with the client device, the performance information, and an inference from a probability distribution over states in accordance with a classification scheme that maps an input attribute vector associated with an input to a confidence that the input belongs to a class, the input relating to at least one of the pattern of files associated with the client device, the series of files associated with the client device, or the performance information, the class corresponding to the configuration information.
10. The device-implemented method of claim 9 , wherein the contextual information further indicates: a pattern of a type of at least one of software, firmware, an application, or an operating system being installed on the client device, or a series of the type.
11. The device-implemented method of claim 9 , wherein the contextual information includes knowledge about a spike in third party searches associated with at least one of at least one hardware issue or at least one software issue; wherein the device-implemented method further comprises: inferring a relationship between the knowledge about the spike in the third party searches and the performance information; and wherein, in response to the inferred causation relationship, providing the configuration information comprises: in response to the inferred relationship between the knowledge about the spike in the third party searches and the performance information, providing, to the client device, the configuration information further based at least in part on the knowledge about the spike in the third party searches.
This invention relates to a device-implemented method for optimizing system performance by analyzing contextual information, including spikes in third-party searches related to hardware or software issues. The method involves collecting performance data from a client device and cross-referencing it with external search trends to identify potential correlations. If a spike in third-party searches about specific hardware or software problems is detected, the system infers a causal relationship between these searches and the client device's performance issues. Based on this inference, the system generates and provides configuration information to the client device, tailored to address the identified problems. The configuration adjustments may include software updates, hardware optimizations, or other corrective measures designed to mitigate the detected issues. The goal is to proactively enhance system performance by leveraging external data trends alongside internal performance metrics.
12. The device-implemented method of claim 9 , wherein, in response to the inferred causation relationship, providing the configuration information comprises: in response to the inferred causation relationship, anticipatorily providing, to the client device, the configuration information.
13. The device-implemented method of claim 9 , wherein the contextual information includes knowledge about a spike in network queries associated with at least one of at least one hardware issue or at least one software issue; wherein the device-implemented method further comprises: inferring a relationship between the knowledge about the spike in the network queries and the performance information; and wherein, in response to the inferred causation relationship, providing the configuration information comprises: in response to the inferred relationship between the knowledge about the spike in the network queries and the performance information, providing, to the client device, the configuration information further based at least in part on the knowledge about the spike in the network queries.
14. The device-implemented method of claim 9 , wherein the contextual information includes knowledge about a spike in messages associated with at least one of at least one hardware issue or at least one software issue; wherein the device-implemented method further comprises: inferring a relationship between the knowledge about the spike in the messages and the performance information; and wherein, in response to the inferred causation relationship, providing the configuration information comprises: in response to the inferred relationship between the knowledge about the spike in the messages and the performance information, providing, to the client device, the configuration information further based at least in part on the knowledge about the spike in the messages.
A method for optimizing device performance by analyzing contextual information related to hardware or software issues involves detecting spikes in message traffic associated with such issues. The method infers a causal relationship between these message spikes and performance data collected from a client device. Based on this inferred relationship, configuration information is provided to the client device to adjust its operation. The configuration information is tailored not only to the performance data but also to the context of the message spike, ensuring more effective troubleshooting or performance enhancement. This approach helps identify and address underlying hardware or software problems that may be impacting device performance, allowing for proactive adjustments to mitigate issues before they escalate. The method leverages real-time data analysis to dynamically configure the device, improving reliability and efficiency.
15. The device-implemented method of claim 9 , further comprising: receiving information associated with at least one social network query performed by at least one third party about at least one of at least one hardware issue or at least one software issue associated with at least one of the contextual information or the performance information; and inferring a relationship between the performance information and the at least one of the at least one hardware issue or the at least one software issue that the at least one social network query is about to obtain correlation information; wherein, in response to the inferred causation relationship, providing the configuration information comprises: in response to the inferred causation relationship, providing, to the client device, the configuration information based at least in part on the correlation information.
16. The device-implemented method of claim 9 , further comprising: receiving information indicating performance of a computing device that is different from the client device; wherein the configuration information is further based at least in part on the information indicating the performance of the computing device.
17. A non-transitory computer-readable storage medium comprising computer executable instructions that, in response to execution, cause a processor-based system to perform operations, the operations comprising: receiving, from a client device, contextual information indicating a pattern of files associated with the client device or a series of files associated with the client device, and performance information indicating at least one of: consumption of memory of the client device, consumption of processor cycles of the client device, configuration of at least one of hardware, software, firmware, or an operating system of the client device, input/output bandwidth of the client device, bandwidth of a network that is communicatively coupled to the client device, or latency associated with the network; inferring a causation relationship between: the pattern of files associated with the client device or the series of files associated with the client device, and the performance information; and in response to the inferred causation relationship, providing, to the client device, configuration information that: identifies at least one of the following, which is configured to improve operating performance of the client device: at least one application, at least one software patch, at least one software update, at least one operating system update, at least one firmware update, or at least one hardware update that is associated with the files and that is configured to improve operating performance of the client device; and is based at least in part on: the pattern of files associated with the client device or the series of files associated with the client device, the performance information, and an inference from a probability distribution over states in accordance with a classification scheme that maps an input attribute vector associated with an input to a confidence that the input belongs to a class, the input relating to at least one of the pattern of files associated with the client device, the series of files associated with the client device, or the performance information, the class corresponding to the configuration information.
18. The non-transitory computer-readable storage medium of claim 17 , wherein the contextual information includes knowledge about a spike in network queries associated with at least one of at least one hardware issue or at least one software issue; and wherein the operations comprise: inferring a relationship between the knowledge about the spike in the network queries and the performance information; and in response to the inferred relationship between the knowledge about the spike in the network queries and the performance information, providing, to the client device, the configuration information further based at least in part on the knowledge about the spike in the network queries.
19. The non-transitory computer-readable storage medium of claim 17 , wherein the contextual information includes knowledge about a spike in messages associated with at least one of at least one hardware issue or at least one software issue; and wherein the operations comprise: inferring a relationship between the knowledge about the spike in the messages and the performance information; and in response to the inferred relationship between the knowledge about the spike in the messages and the performance information, providing, to the client device, the configuration information further based at least in part on the knowledge about the spike in the messages.
20. The non-transitory computer-readable storage medium of claim 17 , wherein the operations comprise: receiving information associated with at least one social network query performed by at least one third party about at least one of at least one hardware issue or at least one software issue associated with at least one of the contextual information or the performance information; inferring a relationship between the performance information and the at least one of the at least one hardware issue or the at least one software issue that the at least one social network query is about to obtain correlation information; and providing, to the client device, the configuration information based at least in part on the correlation information.
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April 13, 2021
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